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SUMMARY:Training course: Data assimilation
DTSTART;VALUE=DATE-TIME:20210510T074500Z
DTEND;VALUE=DATE-TIME:20210514T160000Z
DTSTAMP;VALUE=DATE-TIME:20210420T080714Z
UID:indico-event-208@events.ecmwf.int
DESCRIPTION:Registration for this course is closed.\n\nThis course is a re
mote event.\n\nThis five-day module focuses on describing data assimilatio
n methods and general aspects of assimilating observations. Aspects of the
implementation of the assimilation techniques for real-size numerical wea
ther prediction (NWP) systems will also be described.\n\nAs well as lectur
es there will be discussion and hands-on sessions.\n\nMain topics\n\n\n Th
e fundamental data assimilation concepts\n Optimal Interpolation\, 3D-Var\
, 4D-Var and the Kalman filter\n Ensemble Kalman Filter methods\; Ensemble
of Data Assimilations and uncertainty estimation\; Hybrid variational/ens
emble based methods\n Modelling of error covariances\; handling of non-Gau
ssian errors\n The global observing system\, with emphasis on how to use s
atellite observations\n Bias correction\, quality control and diagnostics\
n Applications of data assimilation methods for the land surface\, ocean\,
atmospheric composition and reanalysis\n\n\nRequirements\n\nParticipants
should have a good meteorological and mathematical background\, and in par
ticular a good understanding of linear algebra. They are expected to be fa
miliar with the contents of standard meteorological and mathematical textb
ooks.\n\nIf you are less familiar with data assimilation concepts\, such a
s Bayes Theorem\, you may wish to consider attending the University of Rea
ding Introductory course\, which runs the week before our course\; see det
ails below.\n\nIntroductory material not covered by the course can be foun
d in our lecture note series.\n\nSome practical experience in numerical we
ather prediction is an advantage.\n\nAll lectures will be given in English
.\n\nhttps://events.ecmwf.int/event/208/
LOCATION:
URL:https://events.ecmwf.int/event/208/
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